This is a LangChain application that uses the [Mistral] 7B model running locally.
We are using Python 3.11 and Poetry to manage environments, make sure you have both installed.
Make sure you have poetry.exe
in your path, and use poetry shell
to open a shell with the environment.
Install dependencies with poetry install
from the root folder.
The project was created with langchain app new .
in the root folder.
Now, if you try to install the PyTorch "wheels" you may note that
the triton
dependency is not available for Windows. Apparently that library
does not have the proper tagging so Poetry does not pick it up
(you can install it from pip
).
There is a workaround for this in the pyproject.toml
file,
pointing to a specific wheel file for a specific Windows, using a specific wheels package:
torch = {url = "https://download.pytorch.org/whl/cu118/torch-2.1.1%2Bcu118-cp311-cp311-win_amd64.whl" }
Normally you would just use the PyTorch cuda wheels for your specific platform, e.g. pulling them from the PyTorch website.
torch = {version = "^2.1.1", source = "pytorch"}
Use poetry show --tree torch
to see the dependency tree.
Install the LangChain CLI if you haven't yet
pip install -U langchain-cli
# adding packages from
# https://github.com/langchain-ai/langchain/tree/master/templates
langchain app add $PROJECT_NAME
# adding custom GitHub repo packages
langchain app add --repo $OWNER/$REPO
# or with whole git string (supports other git providers):
# langchain app add git+https://github.com/hwchase17/chain-of-verification
# with a custom api mount point (defaults to `/{package_name}`)
langchain app add $PROJECT_NAME --api_path=/my/custom/path/rag
Note: you remove packages by their api path
langchain app remove my/custom/path/rag
LangSmith will help us trace, monitor and debug LangChain applications. LangSmith is currently in private beta, you can sign up here. If you don't have access, you can skip this section
export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_API_KEY=<your-api-key>
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
langchain serve
This project folder includes a Dockerfile that allows you to easily build and host your LangServe app.
To build the image, you simply:
docker build . -t my-langserve-app
If you tag your image with something other than my-langserve-app
,
note it for use in the next step.
To run the image, you'll need to include any environment variables necessary for your application.
In the below example, we inject the OPENAI_API_KEY
environment
variable with the value set in my local environment
($OPENAI_API_KEY
)
We also expose port 8080 with the -p 8080:8080
option.
docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app